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Agentic AI · Automation · Sales Enablement
the problem
Pre-call research takes time most sales reps don’t have. Before a discovery call, a good rep needs to know the company, the prospect, the tech stack, the competitive landscape, and the likely objections. In practice that means 30 to 60 minutes of browser tabs, LinkedIn scrolling, and manual note-taking before every single call. The reps who skip it walk in underprepared; the reps who do it properly spend hours a week on work that has nothing to do with actually selling. Either way, the business loses.
the approach
I built a sales research copilot in Relevance AI with three connected tools working in sequence. The first scrapes the company website and returns a structured summary of what the business does, how it positions itself, and what technology it appears to be running. The second takes a LinkedIn URL and builds a prospect profile covering role, background, and likely priorities. The third synthesises both into a structured pre-call report: talking points, relevant context, and suggested angles for the conversation. Reps input a company URL and a LinkedIn profile; the agent handles the rest.
the result
Research time dropped from an hour to minutes. Reps walked into calls with accurate insight into the tech their prospects were already using, which changed how they structured conversations from the first minute. As one rep put it: “Saved me hours pulling data together and gave me a clear picture of the tech already in play. I knew exactly how to structure my calls going in.”